- Visit fmhy.net/android-iosguide#ios-ipas for more sources.
- Sideloading Guide: https://rentry.co/sideloadingguide, https://ios.cfw.guide/sideloading-apps/
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ongkiii
/ IPA-Sources.md
Last active
September 29, 2026 06:00
REPOS/TELEGRAM CHANNELS LIST BY u/angkitbharadwaj
A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.
| Filter | Description | Example |
|---|---|---|
| allintext | Searches for occurrences of all the keywords given. | allintext:"keyword" |
| intext | Searches for the occurrences of keywords all at once or one at a time. | intext:"keyword" |
| inurl | Searches for a URL matching one of the keywords. | inurl:"keyword" |
| allinurl | Searches for a URL matching all the keywords in the query. | allinurl:"keyword" |
| intitle | Searches for occurrences of keywords in title all or one. | intitle:"keyword" |
JPersson77
/ nVAppAppApp.ps1
Last active
September 29, 2026 05:46
nVAppAppApp - workaround NVIDIA DLSS4 whitelisting
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| <# Workaround for NVIDIA's DLSS4 whitelisting | |
| -------- WHAT IS THE BACKSTORY? -------- | |
| DLSS4 was launched alongside the RTX 5000 series and comprise several new and interesting | |
| features, f.e. additional presets for Super Resolution, using a newer Transformer model. | |
| Arguably these features increase image quality significantly. To various degrees these | |
| features are also available for older RTX cards, and older games using DLSS3/2. |
antoniolg
/ jev_server.py
Created
September 18, 2026 13:35
Jev Codex Router server with configurable Luna policy and adaptive effort
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| #!/usr/bin/env python3 | |
| """Jev Codex Router — local server on 127.0.0.1:4319 for the Codex Router. | |
| Receives Responses requests destined for the "jev/auto" model (the Codex | |
| Router's "jev" generic provider), asks Jev (TypeSafe System One) for a tier | |
| and a thinking depth, applies the routing policy, then relays to the Codex | |
| Router's local caller edge (native session sharing enabled) — with no format | |
| conversion: Responses in, Responses out, SSE relayed verbatim. | |
| Default routing policy: |
gadzhimari
/ adobe_cc.md
Created
November 22, 2018 11:29
Completely Remove Adobe from your Mac in 2 Steps
Download and run the Adobe Creative Cloud Cleaner Tool, their multi-app uninstaller and wipe assistant. Adobe does recommend running individual application uninstallers first, your call. Click the Clean All option.
Type a one line command in terminal find ~/ -iname "*adobe*" and it's shows up all files which match pattern.
To remove all files
`sudo rm -rf /Applications/Adobe* /Applications/Utilities/Adobe* /Library/Application\ Support/Adobe /Library/Preferences/com.adobe.* /Library/PrivilegedHelperTools/com.adobe.* /private/var/db/receipts/com.adobe.* ~/Library/Application\ Support/Adobe* ~/Library/Application\ Support/com.apple.sharedfilelist/com.apple.LSSharedFileList.ApplicationRecentDocuments/com.adobe* ~/Library/Application\ Support/CrashReporter/Adobe* ~/Library/Caches/Adobe ~/Library/Caches/com.Adobe.* ~/Library/Caches/com.adobe.* ~/Library/Cookies/com.adobe.* ~/Library/Logs/Adobe* ~/Librar
| name | cognitive-rhythm-writing |
|---|---|
| description | 説明的な文章に緩急を設計するための規範。緩急を装飾ではなく認知モードの切替（観察→逡巡→断定→再観察）と未回収の緊張の管理として扱い、文の拍、段落の密度波形、節の入り方、緩みと駄文の判別、執筆後の機械的な点検手順を定める。読み物として読ませたい章・記事・解説文を生成するとき、または「密度はあるが平坦でおもしろくない」文章を診断・修正するときに使用する。 |
密度の高い文章が退屈になるのは、情報が多いからではなく、全文が同じ認知モードで書かれているからである。 この規範は、読者の認知モード（観察する、迷う、確信する、確かめ直す）を意図的に切り替え、常に「続きを読む理由」を維持することで、読み進める推進力を作る。
| name | japanese-tech-writing |
|---|---|
| description | 日本語の技術文書・書籍原稿の文章規範。段落と論証の構成（パラグラフライティング）、論証の厳密さ（ツッコミどころの除去）、読み手の負荷の管理、視点と語り、演出の抑制、LLM っぽい空句の禁止、翻訳調の比喩と擬人化の禁止（「運ぶ」「効く」「開かれた問い」など）、冗長の排除を定める。日本語で技術書の章、草稿、記事、解説文を書くとき、または推敲・リライトするときに使用する。 |
| license | Unlicense（https://gist.github.com/k16shikano/67625f2a7d96e3bbdfae8d571a936063） |
日本語で技術的な原稿（書籍の章、記事、解説文）を書く・推敲するときは、以下の規範に従う。
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